OpenCV过滤ORB匹配

Question

我使用ORB功能检测器使用此代码查找两个图像之间的匹配:

    FeatureDetector detector = FeatureDetector.create(FeatureDetector.ORB);
    DescriptorExtractor descriptor = DescriptorExtractor.create(DescriptorExtractor.ORB);;
    DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING);

    // First photo
    Imgproc.cvtColor(img1, img1, Imgproc.COLOR_RGB2GRAY);
    Mat descriptors1 = new Mat();
    MatOfKeyPoint keypoints1 = new MatOfKeyPoint();

    detector.detect(img1, keypoints1);
    descriptor.compute(img1, keypoints1, descriptors1);

    // Second photo
    Imgproc.cvtColor(img2, img2, Imgproc.COLOR_RGB2GRAY);
    Mat descriptors2 = new Mat();
    MatOfKeyPoint keypoints2 = new MatOfKeyPoint();

    detector.detect(img2, keypoints2);
    descriptor.compute(img2, keypoints2, descriptors2);

    // Matching

    MatOfDMatch matches = new MatOfDMatch();
    MatOfDMatch filteredMatches = new MatOfDMatch();
    matcher.match(descriptors1, descriptors2, matches);

    // Linking
    Scalar RED = new Scalar(255,0,0);
    Scalar GREEN = new Scalar(0,255,0);

    List<DMatch> matchesList = matches.toList();
    Double max_dist = 0.0;
    Double min_dist = 100.0;

    for(int i = 0;i < matchesList.size(); i++){
        Double dist = (double) matchesList.get(i).distance;
        if (dist < min_dist)
            min_dist = dist;
        if ( dist > max_dist)
            max_dist = dist;
    }



    LinkedList<DMatch> good_matches = new LinkedList<DMatch>();
    for(int i = 0;i < matchesList.size(); i++){
        if (matchesList.get(i).distance <= (1.5 * min_dist))
            good_matches.addLast(matchesList.get(i));
    }



    // Printing
    MatOfDMatch goodMatches = new MatOfDMatch();
    goodMatches.fromList(good_matches);

    System.out.println(matches.size() + " " + goodMatches.size());

    Mat outputImg = new Mat();
    MatOfByte drawnMatches = new MatOfByte();
    Features2d.drawMatches(img1, keypoints1, img2, keypoints2, goodMatches, outputImg, GREEN, RED, drawnMatches, Features2d.NOT_DRAW_SINGLE_POINTS);

    Highgui.imwrite("matches.png", outputImg);

我的问题是我无法找到一种方法来过滤匹配,以便它们只有在照片中具有相似位置时才匹配.我总是得到一个关键点的多个匹配,即使它们位置非常远.

有没有办法更好地过滤它们？

Answer 1

要获得更好的匹配结果,您应该按给定顺序包含这些过滤方法.

1. 在两个方向上执行匹配,即,对于第一图像中的每个点,在第二图像中找到最佳匹配,反之亦然.

2. 在匹配之间执行比率测试(欧几里德距离的比率测试)以消除模糊匹配.

3. 执行RANSAC测试:它是一种模型拟合算法,可找到适合模型的最佳数据并删除异常值.
4. 执行单应性:它是一种图像投影算法.

您可以在计算机视觉应用程序编程手册的第9章中获得上述方法的所有细节.它还有用于实现这些过滤技术的示例代码.这很容易理解.(注意:本书中的代码是用C++编写的,但是一旦理解,它也可以在JAVA中轻松实现)